US 12,462,478 B2
Apparatus and method for generating a three-dimensional (3D) model of cardiac anatomy with an overlay
Abhijith Chunduru, Bengaluru (IN); Uddeshya Upadhyay, Bengaluru (IN); Suthirth Vaidya, Bengaluru (IN); Sai Saketh Chennamsetty, Bengaluru (IN); and Arjun Puranik, San Jose, CA (US)
Assigned to Anumana, Inc., Cambridge, MA (US)
Filed by Anumana, Inc., Cambridge, MA (US)
Filed on Dec. 22, 2023, as Appl. No. 18/395,087.
Prior Publication US 2025/0209737 A1, Jun. 26, 2025
Int. Cl. G06T 17/00 (2006.01); A61B 34/10 (2016.01); G06T 7/55 (2017.01); G06T 7/60 (2017.01); G06T 7/70 (2017.01); G06T 19/20 (2011.01); G16H 30/20 (2018.01); G16H 50/50 (2018.01)
CPC G06T 17/00 (2013.01) [A61B 34/10 (2016.02); G06T 7/55 (2017.01); G06T 7/60 (2013.01); G06T 7/70 (2017.01); G06T 19/20 (2013.01); G16H 30/20 (2018.01); G16H 50/50 (2018.01); A61B 2034/105 (2016.02); G06T 2207/10081 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20092 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30101 (2013.01); G06T 2210/41 (2013.01); G06T 2219/2012 (2013.01)] 24 Claims
OG exemplary drawing
 
1. An apparatus for generating a three-dimensional (3D) model of cardiac anatomy with an overlay, wherein the apparatus comprises:
at least a processor; and
a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to:
receive a set of images of a cardiac anatomy pertaining to a subject, wherein receiving the set of images of the cardiac anatomy comprises extracting the set of images of the cardiac anatomy from a patient profile;
generate a set of shape parameters based on the set of images, wherein generating the set of shape parameters comprises generating the set of shape parameters as a function of the set of images and a shape identification model;
generate a 3D model of the cardiac anatomy based on the set of shape parameters, wherein generating the 3D model includes transforming the 3D model as a function of a plurality of mode changers within a statistical shape model;
generate a map by determining a level of uncertainty at each location of a plurality of locations on the generated 3D model, wherein the map comprises a color-coded heatmap based on one or more levels of uncertainty, wherein each level of the one or more levels of uncertainty is assigned to at least an uncertainty category comprising a pixel-wise uncertainty associated with individual pixels in at least one image of the set of images; and
overlay the map onto the 3D model.